
The challenge is to create a specialized version of a stack with additional capabilities that improve its utility in specific scenarios. Unlike a regular stack which only allows basic operations such as push, pop, and seeking the top element, this task involves designing a MinStack class capable of all those operations plus an intrinsic ability to retrieve the minimum element currently in the stack, all in constant time, O(1). This class should be able to handle potentially dozens of thousands of operations efficiently and must adhere to typical stack operational rules.
Input:
Output:
Explanation:
-2³¹ <= val <= 2³¹ - 1pop, top and getMin operations will always be called on non-empty stacks.3 * 10⁴ calls will be made to push, pop, top, and getMin.To implement all operations in constant time, we use two stacks:
Main Stack (stack):
Min Stack (minStack):
Push (push(val)):
val to stack.minStack is empty or val is less than or equal to the current minimum (minStack.top()), also push val to minStack.Pop (pop()):
stack.minStack.top(), also pop from minStack.Top (top()):
stack.GetMin (getMin()):
minStack.This dual-stack design ensures that:
O(1).minStack.This approach is efficient for large numbers of operations and conforms to the constraints.
The problem "Min Stack" involves creating a stack data structure that supports pushing, popping, and retrieving the smallest element in constant time. The provided C++ solution utilizes two stacks: one for storing all the elements and another auxiliary stack to keep track of the minimum elements.
Here's how the stacks function in the implemented Code:
Functions and their operations:
Constructor (MinStack() {}): Initializes the stacks.
push(int value):
pop():
top():
min():
With this solution, each stack operation (push, pop, top, min) operates in constant time, O(1), which is efficient for scenarios involving frequent stack operations combined with frequent minimum value retrievals.
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